Skip to main content

Deriving qualitative rules from neural networks - a case study for ozone forecasting

Buy Article:

$30.69 plus tax (Refund Policy)

Abstract:

As alternative to physical models, neural networks are a valuable forecast tool in environmental sciences. They can be used effectively due to their learning capabilities and their low computational costs. As far as the relevant variables of the system are measured and put into the network, it works fast and accurately. However, one of the major shortcomings of neural networks is that they do not reveal causal relationships between major system components and thus are unable to improve the explicit knowledge of the user. To overcome this problem, we introduce an approach for deriving qualitative informations out of neural networks. Some of the resulting rules can be directly used by a qualitative simulator for producing possible future scenarios. Because of the explicit representation of knowledge the rules should be easier to understand and can be used as starting point for creating models wherever a physical model is not available. We illustrate our approach using a Network for predicting surface ozone concentrations and discuss open problems and future research directions.

Keywords: Neural network; automatic modelling; ozone forecast; qualitative reasoning

Document Type: Research Article

Affiliations: 1: Technische Universitat Wien, Institut fur Informationssysteme, Database and Artificial Intelligence Group, Favoritenstrasze 9-11, A-1040 Wien, Austria E-mail: wotawadbai.tuwien.ac.at 2: Universitat fur Bodenkultur, Insitut fur Meteorologie und Physik, Turkenschanzstrasze 18, A-1180 Wien, Austria E-mail: wotawaboku.ac.at

Publication date: 2001-01-01

  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more